AIMC Topic: Image Processing, Computer-Assisted

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Self-adaptive deep learning-based segmentation for universal and functional clinical and preclinical CT image analysis.

Computers in biology and medicine
BACKGROUND: Methods to monitor cardiac functioning non-invasively can accelerate preclinical and clinical research into novel treatment options for heart failure. However, manual image analysis of cardiac substructures is resource-intensive and error...

Accuracy of automated forensic dental age estimation lab (F-DentEst Lab) on large Malaysian dataset.

Forensic science international
When a disaster occurs, the authority must prioritise two things. First, the search and rescue of lives, and second, the identification and management of deceased individuals. However, with thousands of dead bodies to be individually identified in ma...

Assessment of image quality and diagnostic accuracy for cervical spondylosis using T2w-STIR sequence with a deep learning-based reconstruction approach.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
OBJECTIVES: To investigate potential of enhancing image quality, maintaining interobserver consensus, and elevating disease diagnostic efficacy through the implementation of deep learning-based reconstruction (DLR) processing in 3.0 T cervical spine ...

Efficient segmentation of active and inactive plaques in FLAIR-images using DeepLabV3Plus SE with efficientnetb0 backbone in multiple sclerosis.

Scientific reports
This research paper introduces an efficient approach for the segmentation of active and inactive plaques within Fluid-attenuated inversion recovery (FLAIR) images, employing a convolutional neural network (CNN) model known as DeepLabV3Plus SE with th...

Developing an explainable diagnosis system utilizing deep learning model: a case study of spontaneous pneumothorax.

Physics in medicine and biology
The trend in the medical field is towards intelligent detection-based medical diagnostic systems. However, these methods are often seen as 'black boxes' due to their lack of interpretability. This situation presents challenges in identifying reasons ...

LD-CSNet: A latent diffusion-based architecture for perceptual Compressed Sensing.

Neural networks : the official journal of the International Neural Network Society
Compressed Sensing (CS) is a groundbreaking paradigm in image acquisition, challenging the constraints of the Nyquist-Shannon sampling theorem. This enables high-quality image reconstruction using a minimal number of measurements. Neural Networks' po...

CBG-Net: Cross-modality and cross-scale balance network with global semantics for multi-modal 3D object detection.

Neural networks : the official journal of the International Neural Network Society
Multi-modal 3D object detection is instrumental in identifying and localizing objects within 3D space. It combines RGB images from cameras and point-clouds data from lidar sensors, serving as a fundamental technology for autonomous driving applicatio...

Dual domain distribution disruption with semantics preservation: Unsupervised domain adaptation for medical image segmentation.

Medical image analysis
Recent unsupervised domain adaptation (UDA) methods in medical image segmentation commonly utilize Generative Adversarial Networks (GANs) for domain translation. However, the translated images often exhibit a distribution deviation from the ideal due...

Multi-degradation-adaptation network for fundus image enhancement with degradation representation learning.

Medical image analysis
Fundus image quality serves a crucial asset for medical diagnosis and applications. However, such images often suffer degradation during image acquisition where multiple types of degradation can occur in each image. Although recent deep learning base...

Automated Method for Intracranial Aneurysm Classification Using Deep Learning.

Sensors (Basel, Switzerland)
Intracranial aneurysm (IA) is now a common term closely associated with subarachnoid hemorrhage. IA is the bulging of a blood vessel caused by a weakening of its wall. This bulge can rupture and, in most cases, cause internal bleeding. In most cases,...